IT and Cybersecurity Resume Reviewer skill

A skill that reviews IT and cybersecurity resumes by evidence: edits from your text, job matching, a PDF report.

  • 190 ★ on the repository
  • Last commit
  • MIT
Skill

Minimal access

Why this level

  • The skill reads a resume and job description and runs local analysis and PDF render scripts. A resume holds personal data and goes to the model provider.
All reasons and checks

mubix/cyber-resume-reviewer-skill

Install

In your terminal, with SkillFoxx CLI

npx skillfoxx add skills/it-and-cybersecurity-resume-reviewer

Detects the agents on your machine, shows the access level and pins the version.

Other ways to install

Access and checks

How we review

Minimal accessThe tool runs nothing and makes no network calls.

  • The skill reads a resume and job description and runs local analysis and PDF render scripts. A resume holds personal data and goes to the model provider.

This is third-party code. Review the repository files before installing.

What it does

Cyber Resume Reviewer reviews IT and cybersecurity resumes without invented achievements. Input is a resume, ideally PDF or DOCX so the agent can check text extraction and layout, plus an optional job description. Output is an editable Markdown report and a styled PDF from the same source. The skill looks at a document through four lenses: machine reading, a human skim, believability and target fit. The report has an assessment, prioritized findings with exact replacements grounded in the source, job fit, format checks and a diagnostic score. A full rewrite mode adapts the resume to a role such as security engineer. A local script `analyze_resume_text.py` reports text signals without hiring conclusions.

Who it is for. IT and cybersecurity professionals preparing a resume for a job application, and recruiters checking resumes for evidence.

Good fit when

  • A cloud security job application needs an assessment of how well the resume fits.
  • Exact wording replacements backed by facts from the source text are needed.
  • A resume is rewritten for a security engineer role without invented metrics.
  • You check how a PDF reads in a parser and what the first impression looks like.
  • Stronger claims need questions to the author instead of guesses.

Not a fit when

  • You need to rank candidates or predict interviews; the skill does not do that.
  • You want missing achievements invented; the skill works only with facts from the source.
  • The resume is outside IT and cybersecurity.

Example request

Use cyber-resume-reviewer: review the attached resume against the job description, give exact edits and do not invent metrics.

Limitations

The skill does not rank candidates, predict interviews or claim an applicant tracking system outcome. If the resume is pasted as text rather than a file, only content is reviewed and layout stays unassessed. Python is needed for the analysis and report scripts. Installation differs by host: Codex, Claude Code, Claude web, Gemini CLI and others have their own paths and upload rules. All materials are in English, and scope is limited to IT and cybersecurity.

How to disable. Delete the `cyber-resume-reviewer` folder from the agent's skills directory: `~/.claude/skills`, `~/.agents/skills` or the project folder.

FAQ

How do I install the skill?

Download `cyber-resume-reviewer.skill` from releases and extract it into the agent's skills folder. Claude web has a separate `cyber-resume-reviewer-claude.zip`, and Gemini CLI uses `gemini skills install`.

Which files should I attach?

A resume in PDF or DOCX so the agent can check text extraction and layout. Pasted text allows only a content review.

Does it invent achievements?

No. The skill uses only facts from the source and moves questions for stronger claims out of the clean resume.

What does the output look like?

An editable Markdown report and a styled PDF from the same source, with prioritized findings and exact replacements.

Does it rank candidates?

No. The skill does not rank people, predict interviews or claim an automated hiring system result.

Discussion

No questions or reviews yet.

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README in short

The root README explains how to prompt, install and port the skill across hosts. The maintainer guide sits inside the skill folder and is excluded from release archives.

README badge

Original SKILL.md

---
name: cyber-resume-reviewer
description: Review, tailor, score, or rewrite IT and cybersecurity resumes. Use for candid critique, job-description fit, exact edits, or complete rewrites; never rank candidates.
metadata:
  version: "4.1.0"
---

# IT and Cybersecurity Resume Reviewer

Improve how the candidate communicates relevant work. Preserve the useful four-lens model: **Machine-read** (document extraction), **Human-skim** (first impression), **Human-believe** (evidence), and **Human-act** (target alignment). These are review lenses, not a universal hiring sequence or a prediction of recruiter behavior.

## Start with the requested deliverable

| Request | Deliver | Default artifact |
|---|---|---|
| Review or improve | Candid verdict, strongest evidence to preserve, prioritized findings, exact edits, and important open questions. Use the standard report template selectively. | Markdown and a PDF rendered from that Markdown |
| Quick review | Up to five material findings and useful exact edits. Omit scoring unless requested. | In conversation, or Markdown when asked |
| Tailor to a JD | Map requirements to evidence, then make truthful changes. Separate employer requirements from assumed role expectations. | Markdown and PDF for a fit report; requested format for a resume rewrite |
| Rewrite / give me an updated resume | Produce the complete rewrite now using established facts. Do not require a full report or another opt-in. Explain material changes briefly. | Rewritten resume in the requested format |
| Score | Use the anchored rubric and show assessed coverage. Score the document, not the person's worth or hiring probability. | Part of the accompanying report |
| JSON | Use the report schema and validator. The analyzer's JSON is a different artifact. | JSON only |
| Interview stories / compare versions | Use the corresponding template only when requested or useful to the stated task. | Markdown unless another format is requested |

## Working sequence

1. **Read the supplied resume and target.** For PDF/DOCX, use available document extraction and rendering capabilities; do not assume specific skill names or tools exist. Read images visually or with OCR, checking uncertain text. Preserve role boundaries, dates, and source locations. If only pasted text is available, assess content and mark visual layout and original-file parsing **Not assessed**.
2. **Resolve only essential uncertainty.** No resume: ask for it. No JD: use a supplied title and label the role profile inferred. A company or industry alone does not define a job. No target: perform a useful general IT/cyber review now; suggest one or two plausible directions and ask which to target before making role-specific claims. Do not withhold all edits.
3. **Triage blockers, risks, and unknowns.** Read [submission triage](references/fatal-flaws-and-kill-checks.md). An observed defect, an explicit unmet requirement, and an unverified fact are different findings. Missing content on a redacted review copy is not a candidate failure.
4. **Build a small evidence map.** Read [review framework](references/review-framework.md). Distinguish candidate-stated facts, job requirements, reviewer inferences, and unknowns. Link every new substantive claim to a resume location or user statement. Do not import facts from another candidate, a sample, the JD, or prior personal context about the reviewer.
5. **Review the relevant role and evidence.** Use the references below selectively. Check scope, ownership, technical meaning, and results. A skill listed without an example is uncorroborated in this document, not automatically false. Specific qualitative outcomes and well-described operational work count; numbers are optional.
6. **Use the text helper when useful.** For a full text review or repeated checks, run `python3 scripts/analyze_resume_text.py --resume resume.txt --jd jd.txt` (omit `--jd` when absent). It finds candidate signals, never ATS acceptance, skill mastery, or hiring odds. Small edits do not need a mandatory script run. Read [helper interpretation](references/analyzer-interpretation.md) before using its output.
7. **Make the changes the user asked for.** Prefer exact source quotes and replacements supported entirely by known facts. Move or merge text without changing its employer, dates, participation level, or context. Place questions for stronger future claims outside the clean rewrite. If essential facts are missing, provide the useful supported portion and identify the limitation.
8. **Produce the artifacts.** Write a full review or JD fit report as Markdown first. Treat it as the only content source, then render the PDF from it. Read [report rendering](references/report-rendering.md) before rendering in a session. Prefer `python3 scripts/render_report.py /path/to/review.md /path/to/resume-review.pdf`; if its dependencies are unavailable, use the host's PDF capability while preserving the same content and visual evidence rules. Save candidate artifacts outside the skill directory. Present both files. If the host cannot create files, provide the complete Markdown in conversation and state that the PDF could not be generated there.
9. **Verify the result.** Check factual traceability, dates, titles, credential status wording, technical meaning, and unresolved placeholders. For a PDF, inspect every rendered page, confirm the page count from the file, and compare extracted reading order with the visual document. Confirm that no `[VERIFY]` token appears in a supported-replacement block. Report only checks actually performed.

## Truth and scope invariants

- Do not invent or upgrade employers, titles, duties, tools, metrics, education, certifications, clearances, authorization, team size, budget authority, board access, or project outcomes.
- Keep **operated / built / supported / led / advised / approved** distinct. Lab, course, volunteer, personal, client, and production work must retain their context. Preserve team attribution.
- Put assumptions in analysis, never as facts inside the resume. No `[Assumed: ...]` claims. For a requested fill-in draft use `[VERIFY: specific fact]`, list every occurrence in a verification table, and label that draft incomplete. Prefer a clean supported version plus optional questions over a resume full of blanks.

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